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Loïc Balazi

Publications and source records attributed to Loïc Balazi.

3 recordsLinked to original sources

Quantum Enhanced Numerical Homogenization

We propose a numerical homogenization method for scalar linear partial differential equations with rough coefficients that integrates classical coarse-scale solvers with quantum subroutines for fine-scale corrections. Inspired by the Localized Orthogonal Decomposition, we employ quantum local problem solvers to capture fine-scale features efficiently. Unlike periodic homogenization approaches, it does not rely on any periodicity assumption. Moreover, the coupling between quantum computation and the coarse model requires only selected measurements of quantum representative volume elements, thereby mitigating the quantum-interface information bottleneck that could otherwise negate a potential speed-up. We show that the local quantum solver can achieve solutions with the required level of accuracy with an operation count that scales only logarithmically with the fine-scale resolution, as determined by the smallest length scale encoded in the diffusion coefficient. The potential of the approach is illustrated through two-dimensional numerical experiments, using a classical simulation of the local quantum solver.

math.NA↗

Neural Network Enhanced Polyconvexification of Isotropic Energy Densities in Computational Mechanics

We present a neural network approach for fast evaluation of parameter-dependent polyconvex envelopes, which are crucial in computational mechanics. Our method uses a neural network architecture that inherently encodes polyconvexity in the main variable by combining a feature extraction layer that computes the minors function on the signed singular value characterisation of isotropic energy densities with a Partially Input Convex Neural Network (PICNN). The envelope inequality is weakly enforced by penalisation during training, as are the symmetries of the function. As a guiding example, we focus on a pseudo time incremental variational damage problem, which is parameter-dependent on previous time-step iterates, the deformation gradient and the internal variable. This problem is reformulated in terms of signed singular values and a splitting approach is applied to reduce the dimension of the parameter space, thereby making training more tractable. Numerical experiments show that the networks achieve favourable accuracy for engineering applications while providing high compression and significant speed-up over traditional polyconvexification schemes. Most importantly, the network adapts to varying physical or material parameters, enabling real-time polyconvexification in large-scale computational mechanics scenarios.

math.NA↗

Effective permeabilities for flow through anisotropic microscopic geometries

This work develops a computational and theoretical framework for determining effective permeabilities in anisotropic microscopic geometries containing dense, fibre-like obstacles, motivated by the need to model flow in coiled aneurysm domains accurately. Building on homogenisation theory and fully resolved simulations in Representative Elementary Volumes (REVs), we validate the permeability model introduced in [C. Boutin, Study of permeability by periodic and self-consistent homogenisation. Eur. J. Mech. A Solids, 19(4):603-632, 2000] and propose a systematic methodology for capturing the directional variations induced by fibre orientation. The resulting permeability tensors are incorporated into macroscopic flow simulations based on the Darcy equation, enabling direct comparison of anisotropic and isotropic permeability models across several benchmark configurations. Our findings show that anisotropy has a significant impact on local flow direction and magnitude, generating directional permeability contrasts which cannot be reproduced by classical isotropic approximations. By integrating coil-induced microstructural effects into continuum-scale hemodynamic models, the proposed approach enables more realistic assessment of post-treatment aneurysm flow behaviour. Beyond this clinical application, the framework is broadly applicable to other biomedical and engineering systems involving fibrous or filamentous porous microstructures.

physics.flu-dyn↗